N.A.W. (Natal) van Riel - Expertise

Riel, N.A.W. van
Address :
Technische Universiteit Eindhoven
P.O. Box 513
Department :
Department of Biomedical Engineering
Section :
Computational Biology
Positioncategory :
Associate Professor (UHD)
Position :
Associate Professor
Room :
GEM-Z 3.109
Tel :
+31 40-247 5506
Tel (internal) :
Email :

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  • D23363 - Geriatrics
  • D23340 - Pharmacology, toxicology
  • D21100 - Bioinformatics, biomathematics
  • D16600 - Artificial intelligence, expert systems
  • Systems biology
  • Systems medicine
  • Metabolism
  • Computational modeling



Prof. Dr. Natal van Riel (1973) is Professor of Computational Modelling at the Academic Medical Center - University of Amsterdam (AMC - UvA) and Associate Professor of Systems Biology and Metabolic Diseases at the Department of Biomedical Engineering of the Eindhoven University of Technology (TU/e). He was trained in system identification and control engineering at the Department of Electrical Engineering, TU/e (MSc degree in 1995). In 2000 he obtained a PhD degree in Molecular Cell Biology from Utrecht University (Prof. Verrips; Netherlands) for research on integrating computational modelling and experiments to study cell metabolism ( PhD thesis ). The research was carried out in the Biotechnology group of Unilever Research Vlaardingen. From 2000 to 2003 he worked in the Department of Electrical Engineering of TU/e investigating the application of system and control theory to understand biological processes. In 2003 he was appointed as Assistant Professor in the Department of Biomedical Engineering at the same university and initiated Systems Biology research in Eindhoven. This research was expanded when he joined the group of Prof. Hilbers in 2006 to lead the Computational Systems Biology research program, investigating complex, multi-factorial diseases. In 2014 he was appointed as Associate Professor. In 2014 he was a visiting scholar of the Department of Bioengineering at the University of California San Diego (UCSD) in the group of Prof. Palsson. His current research focuses on modelling of metabolic networks and physiology, learning algorithms to develop personalized models, methods for analysis of dynamic models, and applications in Metabolic Syndrome and associated diseases such as Type 2 Diabetes.